Beginning Microsoft SQL Server 2008 ... - S3 Tech Training

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Chapter 9: SQL Server Storage and Index Structures As you can see, it looks essentially identical to the more generic B-Trees we discussed earlier in the chapter. In this case, we’re doing a range search (something clustered indexes are particularly good at) for numbers 158–400. All we have to do is navigate to the first record and include all remaining records on that page. We know we need the rest of that page because the information from the node one level up lets us know that we’ll also need data from a few other pages. Because this is an ordered list, we can be sure it’s continuous — that means if the next page has records that should be included, then the rest of this page must be included. We can just start spewing out data from those pages without having to do any verification. We start off by navigating to the root node. SQL Server is able to locate the root node based on an entry that you can see in the system metadata view called sys.indexes. By looking through the page that serves as the root node, we can figure out what the next page we need to examine is (the second page on the second level as we have it drawn here). We then continue the process. With each step we take down the tree, we are getting to smaller and smaller subsets of data. Eventually, we will get to the leaf level of the index. In the case of our clustered index, getting to the leaf level of the index means that we are also at our desired row(s) and our desired data. Non-Clustered Indexes on a Heap 272 I can’t stress enough the importance of this distinction: With a clustered index, when you’ve fully navigated the index, you’ve fully navigated to your data. How much of a performance difference this can make will really show its head as we look at nonclustered indexes — particularly when the non-clustered index is built over a clustered index. Non-clustered indexes on a heap work very similarly to clustered indexes in most ways. They do, however, have a few notable differences: The leaf level is not the data — instead, it is the level at which you are able to obtain a pointer to that data. This pointer comes in the form of a row identifier or RID, which, as we described earlier in the chapter, is made up of the extent, page, and row offset for the particular row being pointed to by the index. Even though the leaf level is not the actual data (instead, it has the RID), we only have one more step than with a clustered index. Because the RID has the full information on the location of the row, we can go directly to the data. Don’t, however, misunderstand this “one more step” to mean that there’s only a small amount of overhead difference and that non-clustered indexes on a heap will run close to as fast as a clustered index. With a clustered index, the data is physically in the order of the index. That means, for a range of data, when you find the row that has the beginning of your data on it, there’s a good chance that the other rows are on that page with it (that is, you’re already physically almost to the next record since they are stored together). With a heap, the data is not linked together in any way other than through the index. From a physical standpoint, there is absolutely no sorting of any kind. This means that from a physical read standpoint, your system may have to retrieve records from all over the file. Indeed, it’s quite possible (possibly even probable) that you will wind up fetching data from the same page several separate times. SQL Server has no way of knowing it will have to come back to that physical location because
there was no link between the data. With the clustered index, it knows that’s the physical sort, and can therefore grab it all in just one visit to the page. Just to be fair to the non-clustered index on a heap here vs. the clustered index, the odds are extremely high that any page that was already read once will still be in the memory cache and, as such, will be retrieved extremely quickly. Still, it does add some additional logical operations to retrieve the data. Figure 9-6 shows the same search we performed on the clustered index, only with a non-clustered index on a heap this time. Through most of the index navigation, things work exactly as they did before. We start out at the same root node, and we traverse the tree dealing with more and more focused pages until we get to the leaf level of our index. This is where we run into the difference. With a clustered index, we could have stopped right here, but with a non-clustered index, we have more work to do. If the non-clustered index is on a heap, then we have just one more level to go. We take the Row ID from the leaf level page and navigate to it. It is not until this point that we are at our actual data. Root Non-Leaf Level Leaf Level Data Pages Figure 9-6 1 2 52 476405 236205 111903 Chapter 9: SQL Server Storage and Index Structures 53 54 103 1 53 104 100403 236201 241905 104 105 156 220701 220702 220703 220704 220701 334205 141604 020001 Ralph Ashley Bill Non-Clustered Indexes on a Clustered Table Looking for Records 158 through 400 With non-clustered indexes on a clustered table, the similarities continue — but so do the differences. Just as with non-clustered indexes on a heap, the non-leaf level of the index looks pretty much as it did for a clustered index. The difference does not come until we get to the leaf level. 1 157 157 158 269 141602 220702 220701 241901 241902 241903 241904 241905 270 271 400 401 Bob Sue Tony George 157 270 410 220703 236204 127504 126003 411 412 236201 236202 236203 236204 236205 151501 102404 Nick Don Kate Tony Francis 273
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Programmer to Programmer Get more
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Beginning Microsoft SQL Ser ver® 2
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Beginning Microsoft SQL Ser ver® 2
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About the Author Experiencing his f
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Acknowledgments Over the years, the
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Contents Chapter 2:T ools of the T
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Contents xviii The CREATE Statement
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Contents xx Correlated Subqueries 1
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Contents xxii SORT_IN_TEMPDB 280 ON
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Contents xxiv Control-of-Flow State
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Contents xxvi How the SQL Ser ver L
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Contents Chapter 16: A Brief XML Pr
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Contents Chapter 19: Pla ying Admin
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Introduction The beginning user wil
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Introduction ❏ We show file names
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Introduction xxxvi ❏ Understand t
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Chapter 1: RDBMS Basics: What Makes
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Chapter 2: Tools of the Trade 22 My
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Chapter 2: Tools of the Trade ❑ S
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Chapter 2: Tools of the Trade 26 Ke
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Chapter 2: Tools of the Trade 28 Th
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Chapter 2: Tools of the Trade 30 lo
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Chapter 2: Tools of the Trade 32 3.
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Chapter 2: Tools of the Trade 34 Fi
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Chapter 2: Tools of the Trade Figur
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Chapter 2: Tools of the Trade Note
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Chapter 2: Tools of the Trade bcp i
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3 The Foundation Statements of T-SQ
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asic SELECT statement. Fire up the
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Now let’s try taking a little bit
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very few of your tables will have s
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Operator Example Usage Effect ALL,
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Chapter 3: The Foundation Statement
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WHERE SalesOrderID IN (43660, 43670
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AVG This one is for computing avera
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efore, but remove the two AS keywor
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You’ll get a result that is a bit
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What if we want to place conditions
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Let’s say, for example, that we w
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City varchar(20) NOT NULL, State ch
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for it in the INSERT statement. For
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And sure enough, we get back the on
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Chapter 4: JOINs 82 returned is in
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Chapter 4: JOINs 84 Using an INNER
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Chapter 4: JOINs 86 Uh, oh — this
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Chapter 4: JOINs How It Works Unlik
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Chapter 4: JOINs If we were to look
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Chapter 4: JOINs 92 What I’m tryi
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Chapter 4: JOINs 16 Mountain-500 Si
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Chapter 4: JOINs 96 Let’s use thi
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Chapter 4: JOINs 98 vendor. We’re
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Chapter 4: JOINs 100 Somehow, we lo
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Chapter 4: JOINs Try It Out FULL JO
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Chapter 4: JOINs Every time I teach
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Chapter 4: JOINs JOIN Sales.Special
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Chapter 4: JOINs Figure 4-1 As alwa
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Chapter 4: JOINs 110 CREATE TABLE U
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Chapter 4: JOINs There are two diff
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Chapter 5: Creating and Altering Ta
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Chapter 6: Constraints At a more sp
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Chapter 6: Constraints We can then
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Chapter 6: Constraints A table can
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Chapter 6: Constraints FOREIGN KEY
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Chapter 6: Constraints How It Works
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Chapter 6: Constraints Cascading Ac
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Chapter 6: Constraints 166 This is
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Chapter 6: Constraints 168 FROM Ord
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Chapter 6: Constraints 170 Let’s
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Chapter 6: Constraints CHECK Constr
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Chapter 6: Constraints Defining a D
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Chapter 6: Constraints Ignoring Bad
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Chapter 6: Constraints Try running
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Chapter 6: Constraints Rules and De
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Chapter 6: Constraints Dropping Rul
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Chapter 6: Constraints 184 Restrict
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7 Adding More to Our Queries When I
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Building a Nested Subquery A nested
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While this works just fine, queries
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We’ll go back to the AdventureWor
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❑ Aliases are used in both querie
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Now let’s see this at work in our
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So let’s take this now and apply
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This join-based syntax, for example
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IF NOT EXISTS (SELECT ‘True’ FR
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The conversions can actually get a
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there are no other roll up records
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GROUP BY soh.OrderDate, sod.Product
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OUTPUT $action, inserted.Year, inse
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The long-standing, traditional view
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8 Being Normal: Normalization and O
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Chapter 8: Being Normal: Normalizat
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Chapter 8: Being Normal: Normalizat
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Chapter 10: Views You can get the y
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11 Writing Scripts and Batches Whet
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Next we have a DECLARE statement to
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I’m not going to pick any bones a
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Using @@IDENTITY @@IDENTITY is one
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How It Works What we’re doing in
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DECLARE @RowCount int; --Notice the
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When the editing tool encounters a
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When you think about it, this seems
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So, let’s try a quick query direc
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We now have our text file source fo
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Let’s build an example in the Adv
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DECLARE @InVar varchar(50); DECLARE
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-- This won’t work DECLARE @Numbe
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-- Now we’re run our conditional
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Out of the condition from inner con
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A Simple CASE A simple CASE takes a
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3 8 More Than One Apart 2 2 Ends Wi
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Now, I don’t know about you, but
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The WAITFOR statement does exactly
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IF @ErrorNo = 2714 -- Object exists
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Chapter 11: Writing Scripts and Bat
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Chapter 12: Stored Procedures Creat
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Chapter 12: Stored Procedures Dropp
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Chapter 12: Stored Procedures Suppl
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Chapter 12: Stored Procedures Confi
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Chapter 12: Stored Procedures Now,
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Chapter 12: Stored Procedures SQL S
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Chapter 12: Stored Procedures It wo
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Chapter 12: Stored Procedures Note
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Chapter 12: Stored Procedures All t
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Chapter 12: Stored Procedures Sproc
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Chapter 12: Stored Procedures When
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Chapter 12: Stored Procedures 400 @
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Chapter 12: Stored Procedures I’d
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Chapter 12: Stored Procedures match
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Chapter 12: Stored Procedures There
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13 User-Defined Functions Well, her
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types!), except for BLOBs, cursors,
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We get back the same set as with th
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AS RETURN (SELECT BusinessEntityID,
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in your relational database. These
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AS BEGIN ( EmployeeID int NOT NULL,
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So, as you can see, we can actually
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Despite being schema-bound, this on
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14 Transactions and Locks This is o
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we are unable or do not want to com
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Figure 14-1 Data needed Data in cac
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Transaction 4 This transaction wasn
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Oops — problem!!! Transaction 2 h
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The only cure for this is setting y
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Exclusive Locks Exclusive locks are
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Also: ❑ The Sch-S is compatible w
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The syntax for switching between th
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As with most things in life, howeve
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purchased. Process 2 records sales;
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Chapter 14: Transactions and Locks
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Chapter 15: Triggers the world’s
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Chapter 15: Triggers WITH ENCRYPTIO
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Chapter 15: Triggers FOR|AFTER The
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Chapter 15: Triggers 458 To illustr
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Chapter 15: Triggers 460 IF EXISTS
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Chapter 15: Triggers ❑ Feeding de
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Chapter 15: Triggers Trigger Firing
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Chapter 15: Triggers Like regular t
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Chapter 15: Triggers The COLUMNS_UP
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Chapter 15: Triggers This is the sa
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Chapter 15: Triggers 472 we have th
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Chapter 16: A Brief XML Primer So,
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Chapter 16: A Brief XML Primer Figu
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Chapter 16: A Brief XML Primer Elem
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Chapter 16: A Brief XML Primer ❑
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Chapter 16: A Brief XML Primer 482
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Chapter 16: A Brief XML Primer Name
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Chapter 16: A Brief XML Primer The
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Chapter 16: A Brief XML Primer 2. W
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Chapter 16: A Brief XML Primer SQL
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Chapter 16: A Brief XML Primer So,
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Chapter 16: A Brief XML Primer If,
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Chapter 16: A Brief XML Primer Note
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Chapter 16: A Brief XML Primer RAW
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Chapter 16: A Brief XML Primer AUTO
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Chapter 16: A Brief XML Primer EXPL
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Chapter 16: A Brief XML Primer Chec
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Chapter 16: A Brief XML Primer The
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Chapter 17: Reporting for Duty, Sir
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Chapter 18: Getting Integrated with
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19 Playing Administrator And so, he
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❑ Write the information to the ev
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Creating Jobs and Tasks Using Manag
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Let’s go ahead and move on to the
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Figure 19-8 Figure 19-9 Chapter 19:
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Figure 19-11 Figure 19-12 Chapter 1
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Backup and Reco very No database-dr
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❑ Differential: This might be ref
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❑ Simple: Under this model, the t
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The older DBCC commands are still s
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many rows inserted over time and th
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Chapter 19: Playing Administrator T
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Appendix A: System Functions In add
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Appendix A: System Functions @@TOTA
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Appendix A: System Functions CHECKS
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Appendix A: System Functions SUM Th
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Appendix A: System Functions The de
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Appendix A: System Functions @@REMS
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Appendix A: System Functions Cert_I
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Appendix A: System Functions Encryp
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Appendix A: System Functions @@FETC
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Appendix A: System Functions CURREN
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Appendix A: System Functions SYSDAT
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Appendix A: System Functions GetRoo
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Appendix A: System Functions The ex
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Appendix A: System Functions RAND T
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Appendix A: System Functions ❑ IN
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Appendix A: System Functions ❑ Is
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Appendix A: System Functions FILEGR
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Appendix A: System Functions INDEX_
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IsCheckCnst IsConstraint IsDefault
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Appendix A: System Functions OBJECT
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Appendix A: System Functions TYPEPR
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Appendix A: System Functions The qu
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Appendix A: System Functions The SU
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Appendix A: System Functions ASCII
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Appendix A: System Functions The ch
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Appendix A: System Functions UNICOD
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Appendix A: System Functions CAST a
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Appendix A: System Functions HOST_I
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Appendix A: System Functions NULLIF
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Appendix A: System Functions 646 Pr
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Appendix A: System Functions Text a
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Appendix B: Very Simple Connectivit
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ABS function A ABS function, 611 AC
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closing tags closing tags, XML docu
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cryptographic functions (continued)
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defects defects. See well formed XM
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EXPLICIT option EXPLICIT option bas
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IGNORE_DUP_KEY option (CREATE INDEX
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LOWER function LOWER function, 635
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online transaction-processing (OLTP
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query results query results alphabe
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scripts (continued) creating with M
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state state, basics of, 391 stateme
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transactions (continued) COMMIT TRA
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View Builder View Builder (Manageme
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